To overcome segmentation difficulties induced by multiple targets of interests

redundant background and inhomogeneous gray levels of the X-ray image

a hierarchical segmentation algorithm based on Mean Shift is proposed. The algorithm is achieved through two layer segmentation. The outer layer segmentation is to locate the positions and determine their regions of interests（ ROI） for all single chips in the X-ray by the matching algorithm with the template of scale invariance and rotation invariance. The inner layer segmentation is to extract subobjects

i. e.

gold lines

balls and PAD of each chip by clustering and analyzing the ROI image and template image using the Mean Shift algorithm. Then calculates mean gray values of gold lines-pattern regions for ROI and template images respectively. Finally

according to the mean gray values of sub-patterns in the template

design an optimized threshold and segment the ROI image by the adaptive threshold segmentation algorithm. The experimental results show that the proposed segmentation algorithm achieves more accurate and reliable results compared with traditional algorithms.